Thesis Details

Deep Learning for Object Detection

Bachelor's Thesis Student: Pitoňák Radoslav Academic Year: 2018/2019 Supervisor: Teuer Lukáš, Ing.

English title

Language

Czech

Abstract

This thesis analyzes different object detection methods which are based on deep neural networks. In the beginning, the convolutional neural networks are described and commonly used object detection methods are compared. In the following parts, the proposal and implementation of the object detection model trained on the specific dataset are described. In conclusion, the achieved results of this model are discussed and compared with the results of other methods.

Keywords

Object detection, deep neural networks, convolutional neural networks, computer vision, BDD, YOLO

Department

Department of Computer Graphics and Multimedia FIT BUT

Degree Programme

Information Technology

Files

Status

defended, grade C

Date

12 June 2019

Reviewer

Dobeš Petr, Ing.

Committee

Čadík Martin, doc. Ing., Ph.D. (DCGM FIT BUT), předseda
Bartík Vladimír, Ing., Ph.D. (DIFS FIT BUT), člen
Bařina David, Ing., Ph.D. (DCGM FIT BUT), člen
Jaroš Jiří, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Kočí Radek, Ing., Ph.D. (DITS FIT BUT), člen

Citation

PITOŇÁK, Radoslav. Deep Learning for Object Detection. Brno, 2019. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2019-06-12. Supervised by Teuer Lukáš. Available from: https://www.fit.vut.cz/study/thesis/17159/

BibTeX

@bachelorsthesis{FITBT17159,
    author = "Radoslav Pito\v{n}\'{a}k",
    type = "Bachelor's thesis",
    title = "Deep Learning for Object Detection",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2019,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/17159/"
}

Theses